1 Introduction

1.1 Motivation

The world’s forcibly displaced population hit its record high in 2017. Globally, at the end of 2017, the global refugee population increased by 2.9 million. By the end of the year, 68.5 million individuals were forcibly displaced worldwide as a result of persecution conflict, or generalized violence (https://www.unhcr.org/5b27be547.pdf). Despite the increase in demand for refugee admission and assistance, the United States specifically has taken a drastic turn away from supporting refugees. The number of refugees admitted to the United States has dropped from a recent high of 84,994 in FY 2016 to 22,874 in FY 2018 - the lowest in 40 years since 1977. The current ceiling for refugee admission has also dropped to 45,000, the lowest in the history of the current US resettlement program. Coming at a time when global numbers of refugees have reached record highs, the ratio of refugees admitted to the United States to the number of refugees worldwide has never been lower. For the first time, the US policy towards refugee admission is moving decisively against the trend of the total number of refugees worldwide (https://www.cgdev.org/blog/reflecting-world-refugee-day-trends-and-consequences-us-refugee-policy). The recent years thus mark a significant shift in refugee resettlement in the US, as a result, this report will be examining the refugee admission trend in the US over the past 10 years (2009-2018).

1.2 Background

According to the UNHCR, refugees are defined as those who have been forced to leave their country due to violence, war, or persecution based on their race, religion, nationality, political opinion or particular social group.

Process of refugee resettlement:

  1. The process of refugee resettlement to the US is a lengthy and thorough process that takes approximately two years and involves numerous US governmental agencies.

  2. Refugees do not choose the country in which they would like to live. UNHCR, the UN Refugee Agency, identifies the most vulnerable refugees for resettlement and then makes recommendations to select countries.

  3. Once a refugee is recommended to the US for settlement, the US government conducts a thorough vetting of each applicant. The process of which takes between 12 to 24 months and includes:
    • Screening by 8 federal agencies including the State Department, Department of Homeland Security and the FBI
    • Six security database checks and biometric security checks screened against US federal databases
    • Medical screening
    • Three in-person interviews with Department of Homeland Security Officers

Under the Refugee Act of 1980, the president sets an annual ceiling for refugee admissions in consultation with Congress. The annual ceiling has varied over the years, from a high of 231,700 in FY 1980 to a prior low of 67,000 in FY 1986. Amid a large exodus of Syrinas from their war-torn country, President Obama raised the refugee ceiling for FY 2016 to 110,000. After taking office, Trump reduced the FY 2017 cap to 50,000, and for FY 2018 set one at a historic low of 45,000. Far fewer refugees, 22,874, were actually resettled in FY 2018.

1.3 Questions

There are currently 25.9 million refugees in the world, indicating the dramatic growth in refugees over the past decade. This led us to question what the refugee resettlement trend has been for the past decade, and delve deeper than just the changes in the numbers of refugees. In order to better visualize the trend of refugee resettlement to the US, this report will be specifically focusing on the top 5 countries (Burma, Iraq, Somalia, Bhutan, Democratic Republic of the Congo) with the highest refugee resettlement population in the US, which accounted for 60.9% of the total refugee arrivals in the US (https://data.newamericaneconomy.org/en/refugee-resettlement-us/).

We are interested in answering the following questions to gain a better understanding of the refugee resettlements in the United States:

  1. What insights can we gain from temporal exploratory data analysis of refugee settlement patterns in the US?
    • Has there been increases/decreases in refugee resettlements population from 2009 - 2018?
    • Is there a correlation between change in refugee resettlement population and major political events that have happened over the 10 years?

  2. What insights can we gain from geographical visualization of refugee settlement patterns in the US over the 10 years? Why might some states have larger refugee settlements than others?

  3. What changes in demographic patterns (i.e., religion, gender, age, etc.) within the refugee population over the 10 years can we visualize?
    • Given the number of religions included in the refugee population, we will be focusing on the top 4 religions in the world (Christianity, Islam, Hinduism, Buddhism). In Iraq, they separate the Muslim population into three categories: Muslim, Muslim Shiite, and Muslim Suni. For the purposes of this analysis, we will combine them as one (https://thecountriesof.com/top-5-largest-religions-in-the-world/).

2 Data Sources

We first collected data from RPC (Refugee Processing Center), that provides refugee arrival information by state and nationality, by destination and nationality, by nationality and religion, and by demographic profile.

We can select the time frame, nationality. Since the RPC website does not allow for faceting by year, we had to download the files year by year, and clean the data into the format we want for data analysis.

3 Data Transformation

3.1 Cleaning the Data in R

  1. From the website, we were able to download ‘.xlsx’ files. Raw files can be found here.
  2. Wrote two functions to clean Excel sheet for a given year.
    1. clean_arrival to clean the Excel files for all refugee resettlements for each state.
    2. clean_demographics to clean the Excel files for demographic information for refugees from specific countries (namely Bhutan, Burma, DRC, Iraq, and Somalia).
  3. Wrote another function, combine_files, to combine each year’s Excel file into one.
  4. Saved these as csv files and uploaded to GitHub to easily access.

3.2 Cleaned Data Format

After cleaning the data, we have six ‘.csv’ files that can be found here.

  1. all_arrivals.csv: The total number of refugee resettlements to each of the 50 states in the US from 2009-2018. All raw files to make this file can be found here.
State Cases Inds Year
California 5524 11512 2009
Texas 3638 8826 2009
New York 2013 5003 2009
Arizona 1952 4543 2009
Florida 1834 4196 2009
Michigan 1602 3460 2009
  1. age_group.csv:
Age.Group Male Female Total country Year
Under 14 1559 1627 3186 Bhutan 2009
Age 14 to 20 1258 1310 2568 Bhutan 2009
Age 21 to 30 1823 1927 3750 Bhutan 2009
Age 31 to 40 1110 1124 2234 Bhutan 2009
Age 41 to 50 726 737 1463 Bhutan 2009
Age 51 to 64 583 626 1209 Bhutan 2009
  1. education.csv:
Education Male Female Total country Year
Bio Data not Complete 2657 1846 4503 Bhutan 2009
Graduate School 21 144 165 Bhutan 2009
Intermediate 509 496 1005 Bhutan 2009
Kindergarten 123 127 250 Bhutan 2009
NONE 100 42 142 Bhutan 2009
Pre-University 1 1 2 Bhutan 2009
  1. ethnicity.csv:
Ethnicity Male Female Total country Year
Lhotsampa 7373 7677 15050 Bhutan 2009
Other 12 15 27 Bhutan 2009
Lhotsampa 5842 5881 11723 Bhutan 2010
Other 3 3 6 Bhutan 2010
Lhotsampa 7314 7410 14724 Bhutan 2011
Other 4 7 11 Bhutan 2011
  1. native_language.csv:
Native.Language Male Female Total country Year
Bio Data not Complete 3 4 7 Bhutan 2009
Dzongka 0 1 1 Bhutan 2009
English 2 1 3 Bhutan 2009
Hindi 1 0 1 Bhutan 2009
Marathi 1 0 1 Bhutan 2009
Napoletano-Calabrese 0 1 1 Bhutan 2009
  1. religion.csv:
Religion Male Female Total country Year
Buddhist 748 853 1601 Bhutan 2009
Christian 534 518 1052 Bhutan 2009
Hindu 5798 5993 11791 Bhutan 2009
Kirat 305 328 633 Bhutan 2009
Buddhist 925 910 1835 Bhutan 2010
Christian 468 453 921 Bhutan 2010

Based on some initial analysis, we decided to exclude Ethnicity and Native language as they did not provide sufficient information to answer our questions regarding refugee resettlement trends in the US. To further elaborate, when we visualized the Ethnicity and Native language trend over the years, the overall trend remained consistent throughout the period, and did not seem to clearly show the refugee resettlement trends unlike the other demographic data we used for analysis.

Furthermore, we excluded many minority religions, as it made it difficult to observe the overall trend due to only a small number of people belonging to each religion. Hence, we concluded that since the majority of the refugees belong to the top-4 religions (Christian, Muslim, Hindu, Buddhist), we decided to focus our analysis on these religions.

3.3 Transforming the Data

In order to visualize and compare the refugee resettlement trends among countries or between years, we had to group the data by country or year.

For the same reason, in addition to using the raw values given in the data (number of people belonging to that group), we transformed the data into proportion to see a clear comparison among the countries, religions, education level, and age.

4 Missing Values

The datasets from RPC (Refugee Processing Center) did not contain any missing values. However, we also noticed that our data contained a single row called “Unknown State”. Since this would not be plotted in our maps, we decided that it would be better to remove the data. Additionally, when we converted the State column to factors, there were 56. The extra 6 states are:

  • American Samoa
  • District of Columbia
  • Guam
  • Puerto Rico
  • Unknown State
  • Virgin Islands

We removed these rows since we are just curious about the fifty states.

In Education data, there were two rows called “Bio Data not Complete” and “Unkown”. We decided to consider these two values as missing data since they do not provide information regarding the education level of the refugees that re-settled in the US. By summing up the total amount of these two rows and dividing it by the total amount of available data, we observed the proportion of missing data compared to the total data.

In the Missing Education Data by Country, Somalia has the largest proportion of data missing among the top-5 countries, with approximately 0.39 of the data missing. Burma has the lowest proportion of data missing, with approximately 0.15 of the data missing.

Similarly, for the Religion data, we also considered the row “NONE” to be missing data, and calculated the proportion of missing data compared to the total data. Unlike the Education data, the proportion of missing data were much smaller. DRC has the most amount of Religion data missing, with approximately 1.19e-03 of the total data missing.

Lastly, Age data did not contain any missing data, so no further analysis was needed to analyze missing patterns for this dataset.

5 Results

5.1 Temporal Analysis

Given our datasets, it is apparent that the temporal patterns of our data are of great importance to our analysis. As a result, to provide a general view of the overall change in resettlement population from 2009 to 2018, we chose to use a time series graph.

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In this graph, we have years on the x-axis, and population count on the y-axis. The green line indicates the ceiling set by the U.S. government for maximum of refugees that can be admitted. The red line indicates the actual number of individuals admitted. We hypothesize that the change in the refugee admission ceiling, and the actual refugee resettlement population are correlated with:

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In this graph, we have years on the x-axis, and population count on the y-axis. The green line indicates the ceiling set by the US government for maximum of refugees that can be admitted. The red line indicates the actual number of individuals admitted. We hypothesize that the change in the refugee admission ceiling, and the actual refugee resettlement population are correlated with:

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  1. The government administration at the time
  2. The US economy and major events in general
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Looking at the general trend of change in refugee admission ceiling, the two timepoints that stand out the most are 2015 and 2016. * In 2015, the refugee admission ceiling increased drastically from 70,000 to a record high of 85,000 in 2016 under President Obama’s administration. * In 2016, however, the refugee admission ceiling decreased drastically from 85,000 to a record low of 45,000 in 2018 under President Trump’s administration and has continued to decrease.

Looking at the general trend of change in the actual refugee resettlement population, we can see that the population decreased from 79,943 in 2009 to a low of 51,458 in 2011, when President Obama was re-elected. However, the resettlement population increased from 51,458 in 2011 to a record high of 96,874 in 2016, and decreased drastically from 96,874 in 2016 to a record low of 22,847 in 2018 under President Trump’s administration.

We take a closer look at the top 5 countries that have refugees resettled in the USA (https://data.newamericaneconomy.org/en/refugee-resettlement-us/).

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Looking at the general trend of change in refugee admission ceiling, the two timepoints that stand out the most are 2015 and 2016. * In 2015, the refugee admission ceiling increased drastically from 70,000 to a record high of 85,000 in 2016 under President Obama’s administration. * In 2016, however, the refugee admission ceiling decreased drastically from 85,000 to a record low of 45,000 in 2018 under President Trump’s administration and has continued to decrease.

Looking at the general trend of change in the actual refugee resettlement population, we can see that the population decreased from 79,943 in 2009 to a low of 51,458 in 2011, when President Obama was re-elected. However, the resettlement population increased from 51,458 in 2011 to a record high of 96,874 in 2016, and decreased drastically from 96,874 in 2016 to a record low of 22,847 in 2018 under President Trump’s administration.

We take a closer look at the top 5 countries that have refugees resettled in the USA (https://data.newamericaneconomy.org/en/refugee-resettlement-us/).

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5.2 Geographical Analysis

5.3 Demographic Analysis

5.3.1 Religion

The top 5 religions in the world are: Christianity, Islam, Hinduism, Buddhism, Sikhism (https://thecountriesof.com/top-5-largest-religions-in-the-world/). In Iraq, they separate the Muslim population into three categories: Muslim, Muslim Shiite, and Muslim Suni. For the purposes of this analysis, we will combine them as one.

5.3.2 Education Level

5.3.3 Age Group

DRC and Somalia have the highest proportions of refugees who are under 14.

6 Interactive Component

6.1 Geographics

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6.2 Demographics: Religion

To dive further into religions of refugees, we visualized the breakdown of Hindu and Muslim refugees over time in the bar charts below. In the drop down menu, the options to select are:

  • All Individuals: count of individuals in each religion by country
  • All Proportions: proportions of each country within a religion

In addition to these two options, there are options to see breakdown of each category by country. For example, “Hindus from Bhutan” means number of Hindu refugees from Bhutan over time. Moreover, “Hindus from Bhutan in Proportions” means proportion of refugees from Bhutan within Hindu refugees over time.

The first bar chart shows that the number of Hindu refugees decreased steadily in the past 10 years, mostly driven by Bhutan. We can observe that refugees from Bhutan account for more than 99% of Hindu refugees, and they decreased from nearly 12,000 to 200, which explains the overall decrease in the past decade.
In the second bar chart, we show the same breakdown among Muslim refugees. In the “All Individuals” chart, we can see that Muslim refugees have dropped drastically since 2017, mainly driven by Iraq and Somalia. This observation is more evident in the individual bar charts for those countries. For example, between 2016 and 2017, Muslim refugees from Iraq decreased by more than 6,000 individuals from 8724 individuals, which is nearly a 75% reduction.

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Through this interactive graph, we can gain a better understanding of the refugee resettlement trends within the US states (2009 - 2018).

In terms of the overall trend, we can observe a significant decrease in overall refugee resettlements in the US from 2009 to 2018. While there was a slight increase from 2015 to 2016, the numbers dropped drastically from 2016 onwards. We can also note that the two states with the largest refugee resettlements are California and Texas, and this has remained constant during the entire period. Interestingly, 2009 was the only year where California accepted more than 9000 refugees. Other states have never exceeded this number.

6.2 Demographics: Religion

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7 Conclusion

TODO: WRITE STUFF